In this study, a methodical qualitative and quantitative analysis of H-Classic publications that have made key contributions and identify intensive mainstream research areas in atomic spectroscopy is presented.
In the past 20 years, spectrometers have shrunk dramatically in size, and this shrinking has been achieved with only modest performance reductions in sampling versatility, spectral range, spectral resolution, and signal-to-noise.
This study shows that surface-enhanced Raman spectroscopy (SERS) of serum can provide an experimental basis for diagnosing leukemia in patients.
In this work, a stable variable selection method based on variable stability correction (VSC) and modified iterative predictor weighting-partial least squares (mIPW-PLS) is proposed for the quantitative analysis of steel samples by laser-induced breakdown spectroscopy (LIBS).
This study uses hyperspectral imaging (HSI) technology, in synergy with machine learning and deep learning algorithms, to innovate a non-destructive method for the assessment of chicken freshness.
We investigate the effect of an applied electric field on the laser-induced titanium plasma for laser induced breakdown spectroscopy (LIBS) for the purpose of assessing electron density with respect to laser energy.
A new method based on singular value decomposition (SVD) applied to the denoising of the time-resolved spectral matrix (TRSM) made it possible to obtain kinetics data of the fluorescence band parameters of a 3-aminophthalimide spectrum in acetonitrile.
Traditional qualitative analysis of agricultural materials using near-infrared spectroscopy can be improved using information-based classification methods, such as projection based on principal components and the Fisher criterion (PPF).
Learn how sub-micron resolution IR microscopy and high-speed spectroscopy overcomes the limitations of Raman spectroscopy for advanced failure analysis applications.
Phosphogypsum can be used as an intermediary material to produce cement clinker. To monitor the quality of phosphogypsum cement, a novel molecular layer deposition X-ray fluorescence (XRF) analysis method using a glass frit was developed.
AFM-IR analyzes nanoscale chemical and complex optical properties of 2D materials, including graphene, hexagonal boron nitride, nanoantennae, and semiconductors.
This method detects elements intrinsically present in cells, and because sc-ICP-TOF-MS measures a full mass spectrum, no analytes are missed.
ATR-FT-IR spectroscopy can provide rapid and portable measurements in forensic applications, demonstrating its ability to rapidly detect biomarkers and the presence of cocaine in fingernails.
We investigate the effect of an applied electric field on the laser-induced titanium plasma for laser induced breakdown spectroscopy (LIBS) for the purpose of assessing electron density with respect to laser energy.
In the agrifood sector, soil sampling and analysis is a prerequisite for accurate fertilizer management and to monitor the accumulation of heavy metals in soils. In this study, energy dispersive X-ray fluorescence (EDXRF) was used to analyze soils with variable textures (clay and sandy) and the percent recovery of elements was compared, as a measure of accuracy.
Detecting illicit drugs in blood samples requires a rapid, non-invasive technique. The combination of surface-enhanced Raman spectroscopy (SERS) and chemometric techniques, such as principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), can aid in this endeavor.
This study describes how interference-free, low-level analysis of toxic elements as well as major elements in particulate matter (PM), with an aerodynamic diameter of 2.5 μm or smaller, can be accomplished. Comparison study examples are given for two locations.
In this study, a methodical qualitative and quantitative analysis of H-Classic publications that have made key contributions and identify intensive mainstream research areas in atomic spectroscopy is presented.
A method combining inductively coupled plasma–mass spectrometry (ICP-MS) with inductively coupled plasma–optical emission spectrometry (ICP-OES) was developed for multielement determination of 50 species of major, minor, micro, and trace, rare earth, and rare elements in geological samples.
Shifted-excitation Raman difference spectroscopy (SERDS) is a technique that is capable of reducing the interference caused by fluorescence and improve the potential of Raman for distinguishing drug compounds in seized samples with fluorescent additives. Here, 43 drugs were analyzed to show the practical application of SERDS.
The details of applying deep learning algorithms and FT-IR spectra are described for classification research using the spectra of strawberries as an example.
PhaseTech's new Volt IR makes e-chem measurements easier because it works in transmission geometry. Plasmonic windows are the electrodes and enhance signals.
This new terahertz method provides a theoretical reference for studying the relationship between biomolecules and water.
In this study, a glycerol-fed, lab-scale E. coli bioprocess producing representative pharmaceutical compounds was monitored offline with a portable, high-sensitivity Raman spectrometer.
Glutathione (GSH) is an intracellular thiol that plays a major role in biological systems. Therefore, the development of effective probes that can detect GSH elicits significant attention.
Peak shifts in infrared spectra may occur for many reasons other than structural changes on the molecular or unit cell level. Here, we discuss several examples.
In X-ray fluorescence (XRF) analysis, physical traceability chains are used to quantify the absolute elemental content in a sample. The physical traceability chain relies on absolute knowledge of the X-ray spectral distribution used for the excitation of the instrument and is currently used at synchrotron radiation facilities. Here, we discuss the transfer of the physical traceability chain to laboratory-based X-ray sources, which are often polychromatic, with the view to generate wider application of quantitative XRF analysis.
A review of exponential signal models with machine learning in nuclear magnetic resonance (NMR) spectroscopy is discussed here.
The implementation of 120 open-path spectroscopy analyzers at oil refineries has taught us lessons about compound identification, target species detectability, interferences, and data management, which can help spectroscopists generate more accurate data when monitoring air quality.